Joint estimation of channel and preamble sequence for orthogonal frequency division multiplexing systems

ABSTRACT

A system includes an estimation module, a processing module, and a control module. The estimation module receives a signal having N sub-carriers and generates N first estimates for channel gains of the N sub-carriers, where N is an integer greater than 1. The processing module generates N second estimates based on the N first estimates. The control module generates N differences between each of the N first estimates and corresponding ones of the N second estimates and estimates (i) a channel gain of the signal and (ii) a preamble sequence in the signal based on the N differences.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.60/783,300, filed on Mar. 17, 2006, U.S. Provisional Application No.,U.S. Provisional Application No. 60/809,733, filed on May 31, 2006, andU.S. Provisional Application No. 60/826,392, filed on Sep. 21, 2006. Thedisclosures of the above applications are incorporated herein byreference in their entirety.

FIELD

The present disclosure relates to communication systems, and moreparticularly to joint estimation of channel and preamble sequences insystems using orthogonal frequency domain multiplexing (OFDM).

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent it is described in thisbackground section, as well as aspects of the description which may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

Referring now to FIG. 1, a typical communication system 10 comprises aninformation source 12, a transmitter 13, a communication channel 20, areceiver 27, and a destination 28. The transmitter 13 comprises a sourceencoder 14, a channel encoder 16, and a modulator 18. The receiver 27comprises a demodulator 22, a channel decoder 24, and a source decoder26.

The information source 12 may be an analog source such as a sensor thatoutputs information as continuous waveforms or a digital source such asa computer that outputs information in a digital form. The sourceencoder 14 converts the output of the information source 12 into asequence of binary digits (bits) called an information sequence u. Thechannel encoder 16 converts the information sequence u into a discreteencoded sequence v called a codeword. The modulator 18 transforms thecodeword into a waveform of duration T seconds that is suitable fortransmission.

The waveform output by the modulator 18 is transmitted via thecommunication channel 20. Typical examples of the communication channel20 are telephone lines, wireless communication channels, optical fibercables, etc. Noise, such as electromagnetic interference, inter-channelcrosstalk, etc., may corrupt the waveform.

The demodulator 22 receives the waveform. The demodulator 22 processeseach waveform and generates a received sequence r that is either adiscrete (quantized) or a continuous output. The channel decoder 24converts the received sequence r into a binary sequence u′ called anestimated information sequence. The source decoder 26 converts u′ intoan estimate of the output of the information source 12 and delivers theestimate to the destination 28. The estimate may be a faithfulreproduction of the output of the information source 12 when u′resembles u despite decoding errors that may be caused by the noise.

Communication systems use different modulation schemes to modulate andtransmit data. For example, a radio frequency (RF) carrier may bemodulated using techniques such as frequency modulation, phasemodulation, etc. In wireline communication systems, a transmitted signalgenerally travels along a path in a transmission line between atransmitter and a receiver. In wireless communication systems, however,a transmitted signal may travel along multiple paths. This is becausethe transmitted signal may be reflected and deflected by objects such asbuildings, towers, airplanes, cars, etc., before the transmitted signalreaches a receiver. Each path may be of different length. Thus, thereceiver may receive multiple versions of the transmitted signal. Themultiple versions may interfere with each other causing inter symbolinterference (ISI). Thus, retrieving original data from the transmittedsignal may be difficult.

To alleviate this problem, wireless communication systems often use amodulation scheme called orthogonal frequency division multiplexing(OFDM). In OFDM, a wideband carrier signal is converted into a series ofindependent narrowband sub-carrier signals that are adjacent to eachother in frequency domain. Data to be transmitted is split into multipleparallel data streams. Each data stream is modulated using asub-carrier. A channel over which the modulated data is transmittedcomprises a sum of the narrowband sub-carrier signals, which mayoverlap.

When each sub-carrier closely resembles a rectangular pulse, modulationcan be easily performed by Inverse Discrete Fourier Transform (IDFT),which can be efficiently implemented as an Inverse Fast FourierTransform (IFFT). When IFFT is used, the spacing of sub-carriers in thefrequency domain is such that when the receiver processes a receivedsignal at a particular frequency, all other signals are nearly zero atthat frequency, and ISI is avoided. This property is calledorthogonality, and hence the modulation scheme is called orthogonalfrequency division multiplexing (OFDM).

Referring now to FIGS. 2A-2C, a wireless communication system 50 maycomprise base stations BS1, BS2, and BS3 (collectively BS) and one ormore mobile stations (MS). Each BS may comprise a processor 30, a mediumaccess controller (MAC) 32, a physical layer (PHY) module 34, and anantenna 36 as shown in FIG. 2B. Similarly, each MS may comprise aprocessor 40, a medium access controller (MAC) 42, a physical layer(PHY) module 44, and an antenna 46 as shown in FIG. 2C. The PHY modules34 and 44 may comprise radio frequency (RF) transceivers (not shown)that transmit and receive data via antennas 36 and 46, respectively.Each BS and MS may transmit and receive data while the MS moves relativeto the BS.

Specifically, each BS may transmit data using orthogonal frequencydivision multiplexing access (OFDMA) system. Each BS may transmit datatypically in three segments: SEG1, SEG2, and SEG3. The MS, which movesrelative to each BS, may receive data from one or more base stationsdepending on the location of the MS relative to each BS. For example,the MS may receive data from SEG 3 of BS1 and SEG 2 of BS2 when the MSis located as shown in FIG. 2A.

Relative motion between MS and BS may cause Doppler shifts in signalsreceived by the MS. This can be problematic since systems using OFDMAare inherently sensitive to carrier frequency offsets (CFO). Therefore,pilot tones are generally used for channel estimation refinement. Forexample, some of the sub-carriers may be designated as pilot tones forcorrecting residual frequency offset errors.

Additionally, the PHY module 34 of each BS typically adds a preamble toa data frame that is to be transmitted. Specifically, the PHY module 34modulates and encodes the data frame comprising the preamble at a datarate specified by the MAC 34 and transmits the data frame. When the PHYmodule 44 of the MS receives the data frame, the PHY module 44 uses thepreamble in the data frame to detect a beginning of packet transmissionand to synchronize to a transmitter clock of the BS.

According to the I.E.E.E. standard 802.16e, which is incorporated hereinby reference in its entirety, a first symbol in the data frametransmitted by the BS is a preamble symbol from a preamble sequence. Thepreamble sequence typically contains an identifier called IDcell, whichis a cell ID of the BS, and segment information. The BS selects thepreamble sequence based on the IDcell and the segment number of the BS.Each BS may select different preamble sequences. Additionally, each BSmay select preamble sequences that are distinct among the segments ofthat BS.

The BS modulates multiple sub-carriers with the selected preamblesequence. Thereafter, the BS performs IFFT, adds a cyclic prefix, andtransmits a data frame. The MS uses the cyclic prefix to perform symboltiming and fractional carrier frequency synchronization. Unless the MSknows the preamble sequence, however, the MS cannot associate itself toa particular segment of a particular BS.

SUMMARY

A system comprises an estimation module, a processing module, and acontrol module. The estimation module receives a signal having Nsub-carriers and generates N first estimates for channel gains of the Nsub-carriers, where N is an integer greater than 1. The processingmodule generates N second estimates based on the N first estimates. Thecontrol module generates N differences between each of the N firstestimates and corresponding ones of the N second estimates. The controlmodule estimates a channel gain of the signal and a preamble sequence inthe signal based on the N differences.

In another feature, the estimation module generates the N firstestimates by dividing the signal by one of i preamble sequences, where iis an integer greater than or equal to 1.

In another feature, the processing module generates each of the N secondestimates by generating weighted averages of the N first estimates.

In another feature, the processing module generates each of the N secondestimates by processing the N first estimates using one of a maximumlikelihood (ML) estimator and a minimum mean square error (MMSE)estimator.

In another feature, the estimation module generates i sets of the Nfirst estimates, where each of the i sets is generated by dividing thesignal by each of the i preamble sequences.

In another feature, the processing module generates i sets of the Nsecond estimates based on the i sets of the N first estimates.

In another feature, the control module generates i sums, where each ofthe i sums is a sum of squares of the N differences in one of the i setsof the N differences.

In another feature, the control module determines a value of i thatgenerates a smallest of the i sums, estimates the preamble sequencepresent in the signal based on the value of i, and estimates the channelgain based on one of the N second estimates that generates the smallestof the i sums.

In another feature, the N sub-carriers are modulated using orthogonalfrequency domain multiplexing (OFDM).

In another feature, every P^(th) one of the N sub-carriers is modulatedwith a preamble symbol from one of i preamble sequences, where P and iare integers greater than or equal to 1.

In another feature, every P^(th) one of the N sub-carriers has one ofsubstantially the same channel phase and substantially the samedifferential channel phase.

In another feature, each of the i preamble sequences is different fromothers of the i preamble sequences, the i preamble sequences have across-correlation value that is less than or equal to a predeterminedthreshold, and the i preamble sequences are stored in one of theestimation and control modules.

In another feature, the predetermined threshold is less thanapproximately 0.2 for an orthogonal frequency domain multiplexing (OFDM)system using a 1024 fast Fourier transform (FFT) mode.

In another feature, the control module identifies a segment of a basestation that transmitted the signal based on the preamble sequencepresent in the signal.

In another feature, a physical layer module (PHY) comprises the systemand further comprises a transceiver module that communicates with theestimation module and that receives the signal.

In another feature, a network device comprises the PHY and furthercomprises at least one antenna that communicates with the transceivermodule.

In still other features, a method comprises receiving a signal having Nsub-carriers, where N is an integer greater than 1, generating N firstestimates for channel gains of the N sub-carriers, and generating Nsecond estimates based on the N first estimates. The method furthercomprises generating N differences between each of the N first estimatesand corresponding ones of the N second estimates, and estimating achannel gain of the signal and a preamble sequence in the signal basedon the N differences.

In another feature, the method further comprises generating the N firstestimates by dividing the signal by one of i preamble sequences, where iis an integer greater than or equal to 1.

In another feature, the method further comprises generating each of theN second estimates by generating weighted averages of the N firstestimates.

In another feature, the method further comprises generating each of theN second estimates by processing the N first estimates using one of amaximum likelihood (ML) estimator and a minimum mean square error (MMSE)estimator.

In another feature, the method further comprises generating i sets ofthe N first estimates, where each of the i sets is generated by dividingthe signal by each of the i preamble sequences.

In another feature, the method further comprises generating i sets ofthe N second estimates based on the i sets of the N first estimates.

In another feature, the method further comprises generating i sums,where each of the i sums is a sum of squares of the N differences in oneof the i sets of the N differences.

In another feature, the method further comprises determining a value ofi that generates a smallest of the i sums, estimating the preamblesequence present in the signal based on the value of i, and estimatingthe channel gain based on one of the N second estimates that generatesthe smallest of the i sums.

In another feature, the N sub-carriers are modulated using orthogonalfrequency domain multiplexing (OFDM).

In another feature, every P^(th) one of the N sub-carriers is modulatedwith a preamble symbol from one of i preamble sequences, where P and iare integers greater than or equal to 1.

In another feature, every P^(th) one of the N sub-carriers has one ofsubstantially the same channel phase and substantially the samedifferential channel phase.

In another feature, the method further comprises storing the i preamblesequences, wherein each of the i preamble sequences is different fromothers of the i preamble sequences, and wherein the i preamble sequenceshave a cross-correlation value that is less than or equal to apredetermined threshold.

In another feature, the predetermined threshold is less thanapproximately 0.2 for an orthogonal frequency domain multiplexing (OFDM)system using a 1024 fast Fourier transform (FFT) mode.

In another feature, the method further comprises identifying a segmentof a base station that transmitted the signal based on the preamblesequence present in the signal.

In another feature, the method further comprises communicating with atransceiver module in a physical layer module (PHY) and receiving thesignal from the transceiver module.

In another feature, the method further comprises communicating with atleast one antenna of a network device comprises the PHY and receivingthe signal via the at least one antenna.

In still other features, a system comprises estimation means forreceiving a signal having N sub-carriers and generating N firstestimates for channel gains of the N sub-carriers, where N is an integergreater than 1. The system further comprises processing means forgenerating N second estimates based on the N first estimates. The systemfurther comprises control means for generating N differences betweeneach of the N first estimates and corresponding ones of the N secondestimates. The control means estimates a channel gain of the signal anda preamble sequence in the signal based on the N differences.

In another feature, the estimation means generates the N first estimatesby dividing the signal by one of i preamble sequences, where i is aninteger greater than or equal to 1.

In another feature, the processing means generates each of the N secondestimates by generating weighted averages of the N first estimates.

In another feature, the processing means generates each of the N secondestimates by processing the N first estimates using one of a maximumlikelihood (ML) estimator and a minimum mean square error (MMSE)estimator.

In another feature, the estimation means generates i sets of the N firstestimates, where each of the i sets is generated by dividing the signalby each of the i preamble sequences.

In another feature, the processing means generates i sets of the Nsecond estimates based on the i sets of the N first estimates.

In another feature, the control means generates i sums, where each ofthe i sums is a sum of squares of the N differences in one of the i setsof the N differences.

In another feature, the control means determines a value of i thatgenerates a smallest of the i sums, estimates the preamble sequencepresent in the signal based on the value of i, and estimates the channelgain based on one of the N second estimates that generates the smallestof the i sums.

In another feature, the N sub-carriers are modulated using orthogonalfrequency domain multiplexing (OFDM).

In another feature, every P^(th) one of the N sub-carriers is modulatedwith a preamble symbol from one of i preamble sequences, where P and iare integers greater than or equal to 1.

In another feature, every P^(th) one of the N sub-carriers has one ofsubstantially the same channel phase and substantially the samedifferential channel phase.

In another feature, each of the i preamble sequences is different fromothers of the i preamble sequences, the i preamble sequences have across-correlation value that is less than or equal to a predeterminedthreshold, and the i preamble sequences are stored in one of theestimation and control means.

In another feature, the predetermined threshold is less thanapproximately 0.2 for an orthogonal frequency domain multiplexing (OFDM)system using a 1024 fast Fourier transform (FFT) mode.

In another feature, the control means identifies a segment of a basestation that transmitted the signal based on the preamble sequencepresent in the signal.

In another feature, a physical layer module (PHY) comprises the systemand further comprises transceiver means for communicating with a medium,wherein the transceiver means communicates with the estimation means andreceives the signal.

In another feature, a network device comprises the PHY and furthercomprises antenna means for receiving signals, wherein the antenna meanscommunicates with the transceiver means.

In still other features, a computer program executed by a processorcomprises receiving a signal having N sub-carriers, where N is aninteger greater than 1, generating N first estimates for channel gainsof the N sub-carriers, and generating N second estimates based on the Nfirst estimates. The computer program further comprises generating Ndifferences between each of the N first estimates and corresponding onesof the N second estimates, and estimating a channel gain of the signaland a preamble sequence in the signal based on the N differences.

In another feature, the computer program further comprises generatingthe N first estimates by dividing the signal by one of i preamblesequences, where i is an integer greater than or equal to 1.

In another feature, the computer program further comprises generatingeach of the N second estimates by generating weighted averages of the Nfirst estimates.

In another feature, the computer program further comprises generatingeach of the N second estimates by processing the N first estimates usingone of a maximum likelihood (ML) estimator and a minimum mean squareerror (MMSE) estimator.

In another feature, the computer program further comprises generating isets of the N first estimates, where each of the i sets is generated bydividing the signal by each of the i preamble sequences.

In another feature, the computer program further comprises generating isets of the N second estimates based on the i sets of the N firstestimates.

In another feature, the computer program further comprises generating isums, where each of the i sums is a sum of squares of the N differencesin one of the i sets of the N differences.

In another feature, the computer program further comprises determining avalue of i that generates a smallest of the i sums, estimating thepreamble sequence present in the signal based on the value of i, andestimating the channel gain based on one of the N second estimates thatgenerates the smallest of the i sums.

In another feature, the N sub-carriers are modulated using orthogonalfrequency domain multiplexing (OFDM).

In another feature, every P^(th) one of the N sub-carriers is modulatedwith a preamble symbol from one of i preamble sequences, where P and iare integers greater than or equal to 1.

In another feature, every P^(th) one of the N sub-carriers has one ofsubstantially the same channel phase and substantially the samedifferential channel phase.

In another feature, the computer program further comprises storing the ipreamble sequences, wherein each of the i preamble sequences isdifferent from others of the i preamble sequences, and wherein the ipreamble sequences have a cross-correlation value that is less than orequal to a predetermined threshold.

In another feature, the predetermined threshold is less thanapproximately 0.2 for an orthogonal frequency domain multiplexing (OFDM)system using a 1024 fast Fourier transform (FFT) mode.

In another feature, the computer program further comprises identifying asegment of a base station that transmitted the signal based on thepreamble sequence present in the signal.

In another feature, the computer program further comprises communicatingwith a transceiver module in a physical layer module (PHY) and receivingthe signal from the transceiver module.

In another feature, the computer program further comprises communicatingwith at least one antenna of a network device comprises the PHY andreceiving the signal via the at least one antenna.

In still other features, the systems and methods described above areimplemented by a computer program executed by one or more processors.The computer program can reside on a computer readable medium such asbut not limited to memory, non-volatile data storage and/or othersuitable tangible storage mediums.

Further areas of applicability of the present disclosure will becomeapparent from the detailed description provided hereinafter. It shouldbe understood that the detailed description and specific examples, whileindicating the preferred embodiment of the disclosure, are intended forpurposes of illustration only and are not intended to limit the scope ofthe disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure will become more fully understood from thedetailed description and the accompanying drawings, wherein:

FIG. 1 is a functional block diagram of an exemplary communicationsystem according to the prior art;

FIG. 2A is a schematic representation of an exemplary wirelesscommunication system comprising three base stations and a mobile stationaccording to the prior art;

FIG. 2B is a functional block diagram of an exemplary base stationutilized in the system of FIG. 2A;

FIG. 2C is a functional block diagram of an exemplary mobile stationutilized in the system of FIG. 2A;

FIG. 3 is a schematic representation of an exemplary wirelesscommunication system comprising three base stations and a mobilestation;

FIG. 4 is a table showing preamble sequences used by base stations ofFIG. 3 to transmit data;

FIG. 5A is a functional block diagram of an exemplary system for jointlyestimating channel gain and preamble sequence according to the presentdisclosure;

FIG. 5B is a graph of channel gain relative to sub-carrier frequency;

FIG. 5C is a graph of channel gain relative to sub-carrier frequencyshowing effect of noise on channel gain;

FIG. 5D is a graph of channel gain relative to sub-carrier frequencyshowing channel gain obtained using weighted average;

FIG. 5E is a graph of channel gain relative to sub-carrier frequencyshowing preliminary channel gain estimates when value of i used toestimate channel gain may be incorrect;

FIG. 5F is a graph of channel gain relative to sub-carrier frequencyshowing channel gain estimates obtained using maximum likelihoodestimator when value of i used to estimate channel gain may beincorrect;

FIG. 6 is a flowchart of an exemplary method for jointly estimatingchannel gain and preamble sequence according to the present disclosure;

FIG. 7A is a functional block diagram of a vehicle control system;

FIG. 7B is a functional block diagram of a cellular phone; and

FIG. 7C is a functional block diagram of a mobile device.

DETAILED DESCRIPTION

The following description is merely exemplary in nature and is in no wayintended to limit the disclosure, its application, or uses. For purposesof clarity, the same reference numbers will be used in the drawings toidentify similar elements. As used herein, the term module, circuitand/or device refers to an Application Specific Integrated Circuit(ASIC), an electronic circuit, a processor (shared, dedicated, or group)and memory that execute one or more software or firmware programs, acombinational logic circuit, and/or other suitable components thatprovide the described functionality. As used herein, the phrase at leastone of A, B, and C should be construed to mean a logical (A or B or C),using a non-exclusive logical or. It should be understood that stepswithin a method may be executed in different order without altering theprinciples of the present disclosure.

Referring now to FIG. 3, a wireless communication system 100 maycomprise base stations BS1, BS2, and BS3 (collectively BS) and one ormore mobile stations (MS). Generally, one MS may communicate with up tothree adjacent base stations. Each BS may transmit data that ismodulated using an orthogonal frequency division multiplexing access(OFDMA) system.

Specifically, each BS may transmit data in three segments: SEG1, SEG2,and SEG3. The MS, which may move relative to each BS, may receive datafrom one or more base stations depending on the location of the MSrelative to each BS. For example, the MS may receive data from SEG 3 ofBS1, SEG 2 of BS2, and/or SEG 1 of BS3 when the MS is located as shown.

When a receiver in the MS is turned on (i.e., when the MS is poweredup), the MS may associate with an appropriate segment of a correspondingBS depending on the location of the MS. The MS, however, can processdata in a frame transmitted by a BS only if the MS can correctly detecta preamble sequence in the frame. Specifically, the MS can perform framesynchronization and retrieval of a cell ID (IDcell) and a segment numberof the BS from the frame if the MS can detect the preamble sequence inthe frame.

Referring now to FIG. 4, OFDMA systems may use 1024 and 512 sub-carriersto modulate and transmit data. OFDMA systems using 1024 and 512sub-carriers are generally referred to as OFDMA systems having 1024 and512 FFT modes, respectively. Additionally, I.E.E.E. 802.16e supports 128FFT and 2048 FFT modes.

A total of 114 preamble sequences exist for OFDMA systems that use fastFourier transforms (FFT) to modulate 1024 and 512 sub-carriers. Eachpreamble sequence is unique. That is, each preamble sequence is distinctfrom another preamble sequence and is identified by an index number. Theindex number may be referred to as preamble sequence index. Eachpreamble sequence is 284 and 143 bits (symbols) long for 1024 and 512FFT modes, respectively.

Since one MS may typically communicate with up to three base stations,each BS modulates every third sub-carrier. That is, each BS modulatesone of every three sub-carriers. Additionally, each BS uses only one bitof the total bits in a preamble sequence when modulating every thirdsub-carrier. For example, in 1024 FFT mode, the BS may use bit numbers1, 2, 3, . . . , etc., of the 284 bits in a preamble sequence tomodulate sub-carrier numbers 1, 4, 7, . . . , etc., of the 1024sub-carriers, respectively.

Each BS may use the same set of sub-carriers. Each segment in a BS,however, uses distinct sub-carriers at least for preamble purposes. Forexample, for each BS, segment 1 (SEG1) may use sub-carriers 0, 3, 6, 9,. . . , etc.; segment 2 (SEG2) may use sub-carriers 1, 4, 7, 10, . . . ,etc.; and segment 3 (SEG3) may use sub-carriers 2, 5, 8, 11, . . . ,etc.

Consequently, the MS receives distinct signals from each BS. Forexample, the MS may receive signals from SEG2 of BS2 on sub-carriers 1,4, 7, 10, . . . , etc., from SEG1 of BS3 on sub-carriers 0, 3, 6, 9, . .. , etc., and from SEG 3 of BS1 on sub-carriers 2, 5, 8, 11, . . . ,etc. Thus, the signals received by the MS may not interfere with eachother since their sub-carriers are distinct.

A set of sub-carriers for segment n may be mathematically expressed asfollows.PreambleCarrierSet_(n) =n+3kwhere 0≦k≦283 for 1024 FFT mode and 0≦k≦142 for 512 FFT mode.Additionally, there may be 86 guard sub-carriers on the left and rightends of the spectrum in 1024 FFT mode. In the 512 FFT mode, there may be42 guard sub-carriers on the left end and 41 guard sub-carriers on theright end.

Typically, when the receiver in the MS is turned on, the MS initiallyperforms symbol timing and carrier frequency synchronization before theMS can detect a preamble sequence. The MS may perform these tasks usinga cyclic prefix in the data frame. Thereafter, the MS determines whethera first symbol in the frame is a preamble symbol. If the first symbol isa preamble symbol, then the MS determines which preamble sequence ispresent in the frame. Once the MS determines the preamble sequence, theMS can associate with a corresponding segment of an appropriate BS.

Symbols in preamble sequences (i.e., preamble symbols) typically havehigher energy than data symbols. For example, the energy of the preamblesymbols is typically 8/3 times (i.e., 4.26 dB higher than) the energy ofdata symbols. This is useful in distinguishing preamble symbols fromdata symbols.

Additionally, the preamble sequences are almost orthogonal. That is, across-correlation between any two preamble sequences is very small. Forexample, the cross-correlation is typically less than 0.2. This isuseful in distinguishing individual preamble sequences from one another.As shown in the table in FIG. 4, if the MS detects a preamble sequencehaving an index 0, then the MS associates with segment 0 of BS havingcell ID 0, and so on.

Base stations and mobile stations may be configured to operate in WiMAXwireless networks. WiMAX is a standards-based technology that enableswireless broadband access as an alternative to wired broadband likecable and DSL. WiMAX provides fixed, nomadic, portable, and mobilewireless connectivity without a direct line-of-sight with a basestation. WiMAX technology may be incorporated in portable electronicdevices such as notebook computers, personal digital assistants (PDAs),etc.

When WiMAX-compliant mobile stations receive signals, a preamblesequence in the received signals can be detected and identified if thechannel is known. In that case, the received signals can be equalized bythe channel and can be correlated with all preamble sequences to find amatch. Alternately, if the preamble sequence received in the receivedsignal is known, the channel can be calculated. In that case, thepreamble sequence is initially estimated, and the channel is calculatedbased on the estimated preamble sequence. In WiMAX systems, however,preamble sequences transmitted by base stations and channel are unknownto the mobile stations.

Referring now to FIGS. 5A-5F, a system 160 for jointly estimating bothpreamble sequence and channel in a mobile station (MS) may beimplemented in a physical layer (PHY) module 162 of the MS. The system160 comprises an estimation module 164, a processing module 165, and acontrol module 166 as shown in FIG. 5A. The estimation module 164receives an input signal transmitted by a base station (BS). The inputsignal may be mathematically expressed as follows.Y[k]=H[k]X _(i) [k]+Z[k]where k is sub-carrier index, i is preamble sequence index, Y[k] isreceived input signal, H[k] is channel gain, X_(i)[k] is transmitsignal, and Z[k] is noise.

When a preamble bit (i.e., a preamble symbol) in a preamble sequence is0, the corresponding transmit signal X_(i)[k] is 1. When a preamble bitin a preamble sequence is 1, the corresponding transmit signal X_(i)[k]is −1. That is, when a preamble bit in a preamble sequence is 1, thechannel phase of the sub-carrier in the transmit signal X_(i)[k] isshifted by π relative to the channel phase of the sub-carrier when apreamble bit in a preamble sequence is 0.

When input signals have high signal-to-noise ratio (SNR), noise Z[k] maybe negligible. In that case, the noise Z[k] may be disregarded, and thechannel gain H[k] may be given by the following equation.H[k]=Y[k]/X _(i) [k]

As shown in FIG. 5B, the channel gain H[k] (hereinafter channel) mayvary across N sub-carriers, where N=1024 for 1024 FFT mode. The channel,however, may not vary significantly between adjacent modulatedsub-carriers. For example, the variation in channel between sub-carriers0 and 3, between sub-carriers 3 and 6, etc. may be small. In that case,the channel may be considered frequency flat.

Assuming i=0, that is, assuming that the input signal comprises a firstpreamble sequence having an index 0, the estimation module 164 generatespreliminary channel estimates H′₀[k]=Y[k]/X₀[k] for each sub-carrier bydividing the input signal Y[k] by the first preamble sequence X₀[k].Thus, the preliminary channel estimate H′₀[0] is an estimate of thechannel for sub-carrier 0, the preliminary channel estimate H′₀[3] is anestimate of the channel for sub-carrier 3, etc. In other words,H′_(0[)0] is the estimate of the channel at point 170, H′₀[3] is theestimate of the channel at point 173, etc. Similarly, the estimationmodule 164 generates preliminary channel estimates for each i. The ipreamble sequences, where 0≦i≦113 for 1024 FFT mode, may be stored inthe estimation module 164 or the control module 166.

The processing module 165 processes the preliminary channel estimatesand generates processed channel estimates H″_(i)[k] as follows.H″ _(i) [k]=f(H′ _(i)(0),H′ _(i)(1),H′ _(i)(1023)).That is, the processing module 165 generates H″_(i)[k] for eachsub-carrier by processing the preliminary channel estimates H′_(i)(0),H′_(i)(1), H′_(i)(1023).

If the channel is frequency flat, the processing module 165 may generateH″_(i)[k] by generating a weighted average of a predetermined number ofsub-carriers that are adjacent to the sub-carrier for which H″_(i)[k] iscalculated. For example, H″_(i)[6] may be calculated by averagingH′_(i)[3], H′_(i)[6], and H′_(i)[9]. Alternately, the processing module165 may generate H″_(i)[k] by using a maximum likelihood (ML) estimator,a minimum mean square error (MMSE) estimator, etc.

As shown in FIG. 5C, the preliminary channel estimates H′_(i)[k] denotedby squares at 180, 183, . . . , etc. may differ from actual channelvalues due to noise. In that case, using averaging or other estimatorsto generate H″_(i)[k] may improve the estimation as shown in FIG. 5D bytriangles at 190, 193, . . . , etc. That is, the processed channelestimates H″_(i)[k] denoted by triangles may be closer to the actualvalues of the channel than the preliminary channel estimates H′_(i)[k]denoted by squares.

If the input signal in fact includes the preamble sequence assumed to bepresent in the input signal, the values of H″_(i)[k] may differ onlyslightly from H′_(i)[k]. That is, the difference between respectiveprocessed and preliminary channel estimates (i.e., triangles andsquares, respectively) may be minimum, and the difference may representnoise.

On the other hand, if the input signal does not include the preamblesequence assumed to be present, the values of H′_(i)[k] denoted bysquares at 200, 203, . . . , etc. in FIG. 5E may differ widely fromactual channel values as shown. Consequently, the processed channelestimates H″_(i)[k] denoted by triangles at 210, 213, . . . , etc. inFIG. 5F may also differ widely from H′_(i)[k] as shown. Thus, thedifference between respective processed and preliminary channelestimates (i.e., triangles and squares, respectively) may be high.

The control module 166 calculates the difference between H″_(i)[k] andH′_(i)[k], generates an absolute value of the difference (or error inestimates), |H″i[k]−H′_(i)[k]|, and generates squared error,|H″_(i)[k]−H′_(i)[k]|². Thus, the estimation module 164 generatesestimates H′_(i)[k] for all i, the processing module 165 generatesH″_(i)[k] for all i, and the control module 166 generates|H″_(i)[k]−H′_(i)[k]|² for all i. The control module 166 generates a sumof all |H″_(i)[k]−H′_(i)[k]|² values for each i. The value of i forwhich the sum of |H′_(i)[k]−H″_(i)[k]|² values is minimum is theestimate for the index i of the preamble sequence present in the inputsignal received by the MS.

This is mathematically expressed as follows.

$\hat{i} = {\underset{i}{\arg\;\min}{\sum\limits_{k = 0}^{N - 1}{{{H_{i}^{''}\lbrack k\rbrack} - {H_{i}^{\prime}\lbrack k\rbrack}}}^{2}}}$where N=1024 and 0≦i≦113 for 1024 FFT mode. Additionally, the value ofH″_(i)[k] for which the sum of |H″_(i)[k]−H′_(i)[k]|² values is minimumis the estimate of the channel. Thus, the control module 166simultaneously estimates the preamble sequence index and the channel.Additionally, since each preamble sequence is unique, the control module166 implicitly estimates which segment of a base station transmitted thepreamble sequence when the control module 166 estimates the preamblesequence index.

Referring now to FIG. 6, a method 250 for jointly estimating bothpreamble sequence and channel in an input signal received by a mobilestation (MS) begins at step 252. In step 254, a preamble sequence havingan index i=0 is assumed to be present in an input signal received by theMS. An estimation module 164 generates preliminary estimates H′_(i)[k]in step 256. A processing module 165 generates processed estimatesH″_(i)[k] from H′_(i)[k] using weighted averages, maximum likelihoodestimator, or minimum mean square error estimator, etc. in step 258.

A control module 166 generates an absolute value of the differencebetween processed and preliminary channel estimates|H″_(i)[k]−H′_(i)[k]| in step 260. The control module 166 generates asum of |H″_(i)[k]−H_(i)[k]|² values for all k in step 262. The controlmodule 166 checks in step 264 if the sum has been calculated for all i.If false, the value of i is incremented in step 266, and steps 256through 264 are repeated.

If true, the control module 166 estimates in step 268 that the value ofi that generated a smallest sum of |H″_(i)[k]−H′_(i)[k]|² values is thepreamble sequence index for the preamble sequence present in the inputsignal. Additionally, the control module 166 simultaneously estimates instep 270 that the value of H″_(i)[k] in the smallest sum is the channelestimate. The method 250 ends in step 272.

Although the present disclosure describes joint estimation of channeland preamble sequence for mobile stations having a single receiveantenna, skilled artisans can appreciate that the joint estimation canbe extended to mobile stations having multiple receive antennas.Specifically, for mobile stations having M receive antennas, thepreliminary channel estimates may be denoted by H′_(i,m)[k], where m isthe antenna index, and the processed channel estimates H″_(i,m)[k] maybe expressed as a function of H′_(i,m)[k].

In that case, the value of i for which the sum of|H′_(i,m)[k]−H″_(i,m)[k]|² values is minimum is the estimate for theindex i of the preamble sequence present in the input signal received bythe mobile station having M receive antennas. This is mathematicallyexpressed as follows.

$\hat{i} = {\underset{i}{\arg\;\min}{\sum\limits_{m = 0}^{M - 1}{\sum\limits_{k = 0}^{N - 1}{{{H_{i,m}^{''}\lbrack k\rbrack} - {H_{i,m}^{\prime}\lbrack k\rbrack}}}^{2}}}}$where N=1024 and 0≦i≦113 for 1024 FFT mode.

The value of H″_(i,m)[k] for which the sum of |H″_(i,m)[k]−H′_(i,m)[k]|²values is minimum is the estimate of the channel. Thus, the preamblesequence index and the channel can be jointly estimated in mobilestations having multiple receive antennas. Additionally, since eachpreamble sequence is unique, the joint estimation implicitly estimateswhich segment of a base station transmitted the preamble sequence whenthe preamble sequence index is estimated.

As an example, joint estimation of preamble sequence and channel usingmaximum likelihood (ML) estimator may be mathematically described asfollows. The following notational conventions are hereinafter used. Anuppercase letter denotes a frequency domain signal, a lowercase letterdenotes a time domain signal, and a bold-faced character denotes arandom quantity.

An OFDM system transmits information as a series of OFDM symbols. Aninverse discrete Fourier transform (IDFT) is performed on N informationsymbols denoted by X[m, k] for k=0, 1, . . . , N−1, and cyclic prefixsamples of length N_(g) are prepended, where m represents an OFDM symbolnumber, and k represents a sub-carrier number.

The time domain samples x[m, n] of m^(th) OFDM symbol are expressed asfollows.

${x\left\lbrack {m,n} \right\rbrack} = \left\{ \begin{matrix}{{\frac{1}{N}{\sum\limits_{k = 0}^{N - 1}{{X\left\lbrack {m,k} \right\rbrack}{\mathbb{e}}^{j\frac{2\pi\; k\; n}{N}}}}},{{{for} - N_{g}} \leq n \leq {N - 1}}} \\{0,\mspace{315mu}{{elsewhere}.}}\end{matrix} \right.$

The OFDM symbol x[m, n] is transmitted through a channel h[m, n], whichmay be corrupted by Gaussian noise z[m, n]. The channel h[m, n] isassumed to be block-stationary, i.e., time-invariant during each OFDMsymbol. Additionally, the channel h[m, n] is assumed to have finiteduration such that h[m, n]=0 for n<0 and for n>N_(g). Based on theseassumptions, an output y[m, n] of a channel may be given by followingequation.

${{y\left\lbrack {m,n} \right\rbrack} = {{\sum\limits_{r = 0}^{N_{g}}{{h\left\lbrack {m,r} \right\rbrack}{x\left\lbrack {m,{n - r}} \right\rbrack}}} + {z\left\lbrack {m,n} \right\rbrack}}},$where z[m, n] is additive white Gaussian noise (AWGN) with variance σ²_(z).

Assuming that preamble sequences occupy one OFDM symbol, only one OFDMsymbol may be examined for jointly estimating preamble sequence andchannel. Since only one OFDM symbol is examined, the OFDM symbol index mis hereinafter omitted.

A received input signal may be expressed in frequency domain as follows.Y[k]=H[k]X _(i) [k]+Z[k],where Z[k] is Gaussian noise, X_(i)[k] is k^(th) value of i^(th)preamble sequence, and

${H\lbrack k\rbrack} = {\sum\limits_{n = 0}^{N_{g}}{{h\lbrack n\rbrack}{{\exp\left( \frac{{- {j2\pi}}\;{kn}}{N} \right)}.}}}$

Alternatively, the received input signal may be represented in avector-matrix notation by the following equation.Y=X _(i) H+Z,where Y=[Y[0] Y[1] . . . Y[N−1]]^(T), and H and Z are similarly defined.X_(i) is a diagonal matrix whose diagonal is given by [X_(i)[0] X_(i)[1]. . . X_(i)[N−1]].

Since H[k] is a discrete Fourier transform of channel h[n] and thechannel h[n] is of finite duration, the received input signal can berepresented in terms of h=[h[0] h[1] . . . h[Ng]]^(T) as follows.Y=X _(i) √{square root over (N)}FI _(N,N) ₉ ₊₁ h+Z,where F is a discrete Fourier matrix of size N×N whose element (m,n)^(th) element is

$F_{m,n} = {\frac{1}{\sqrt{N}}{{\exp\left( {- \frac{2{\pi\left( {m - 1} \right)}\left( {n - 1} \right)}{N}} \right)}.}}$

For m≧n, I_(N,N) _(g) ₊₁ is defined as follows.

${I_{m,n}{\underset{=}{\bigtriangleup}\begin{bmatrix}I_{m} \\O_{m - n}\end{bmatrix}}},$where I_(n) is an identity matrix and O_(n) is a zero matrix, each ofsize n×n. On the other hand, for m<n,I_(m,n)

[I_(m)O_(n-m)].

A joint ML estimator for estimating both i and h from Y=Y is given bythe following equation.

${\left( {\hat{h},\hat{i}} \right) = {\underset{({h,i})}{\arg\;\max}{f_{{Y|h},i}\left( {\left. Y \middle| h \right.,i} \right)}}},$where f_(Y|h,i)(Y|h,i) is a conditional probability density function ofY given h=h and i=i. Since noise Z is a circularly symmetric complexGaussian vector whose elements have mean of zero and variance σ² _(z),the conditional probability density function is given by

${f_{{Y|h},i}\left( {\left. Y \middle| h \right.,i} \right)} = {\frac{1}{\left( {{\pi\sigma}\underset{z}{2}} \right)^{N}}{{\exp\left( \frac{- {{Y - {X_{i}\sqrt{N}{FI}_{N,{N_{g} + 1}}h}}}^{2}}{\sigma_{z}^{2}} \right)}.}}$

Since an exponential function e^(−x) is a monotonically decreasingfunction of x, maximizing f_(Y|h,i)(Y|h,i) is equivalent to minimizingthe following square error.S(h,i)=∥Y−X _(i) √{square root over (N)}FI _(N,N) _(g) ₊₁ H∥ ²

Now the problem of finding (h, i) that minimizes S(h, i) can be solvedin two steps as follows. In a first step, for each possible i, a channelestimate h^(i) that minimizes S(h, i) is found. Second, from the h^(i)'sfound in the first step, i^ that minimizes S(h^(i), i) is selected.Additionally, h^(i^) is selected as an estimate for h. In other words,

$\begin{matrix}{{{\hat{h}(i)} = {\underset{h}{\arg\;\min}\left\{ {S\left( {h,i} \right)} \right\}}},} \\{{\hat{i} = {\underset{i}{\arg\;\min}\left\{ {S\left( {{h(i)},i} \right)} \right\}}},}\end{matrix}$and ĥ=ĥ(î).

The channel estimate h^(i) for a given i that minimizes S(h, i) can beeasily derived by solving a least-square estimation problem as follows.LetA _(i) =X _(i) √{square root over (N)}FI _(N,N) _(g) ₊₁.Therefore, ĥ(i)=A_(i) ^(†)Y,where A_(i) ^(†)=(A_(i) ^(H)A_(i))⁻¹A_(i) ^(H) represents apseudo-inverse of A (i.e., A^(†)A=I), and A_(i) is a full rank matrix.

A corresponding square error S(h^(i), i) for the channel estimate h^(i)is given byS(ĥ(i)=∥Y−A _(i) A _(i) ^(†) Y∥ ².Thus, for every i, the square error S(h^(i), i) is calculated. Apreamble sequence index i that minimizes the square error S(h^(i), i) isselected. A final channel estimate is the channel estimate thatcorresponds to the preamble sequence index that minimizes the squareerror. This channel estimate is the channel estimate in time domain. Achannel estimate in frequency domain is given by performing fast Fouriertransform (FFT) on the channel estimate in time domain. Thus, Ĥ=√{squareroot over (N)}Fĥ.

Although ML estimate is described, skilled artisans can appreciate thatother estimators may be used to jointly estimate preamble sequence andchannel. For example, a minimum mean square error (MMSE) estimator maybe used to jointly estimate preamble sequence and channel.

Referring now to FIGS. 7A-7C, various exemplary implementationsincorporating the teachings of the present disclosure are shown.Referring now to FIG. 7A, the teachings of the disclosure may beimplemented in a WiMAX interface 452 of a vehicle 446. The vehicle 446may include a vehicle control system 447, a power supply 448, memory449, a storage device 450, and the WiMAX interface 452 and associatedantenna 453. The vehicle control system 447 may be a powertrain controlsystem, a body control system, an entertainment control system, ananti-lock braking system (ABS), a navigation system, a telematicssystem, a lane departure system, an adaptive cruise control system, etc.

The vehicle control system 447 may communicate with one or more sensors454 and generate one or more output signals 456. The sensors 454 mayinclude temperature sensors, acceleration sensors, pressure sensors,rotational sensors, airflow sensors, etc. The output signals 456 maycontrol engine operating parameters, transmission operating parameters,suspension parameters, etc.

The power supply 448 provides power to the components of the vehicle446. The vehicle control system 447 may store data in memory 449 and/orthe storage device 450. Memory 449 may include random access memory(RAM) and/or nonvolatile memory such as flash memory, phase changememory, or multi-state memory, in which each memory cell has more thantwo states. The storage device 450 may include an optical storage drive,such as a DVD drive, and/or a hard disk drive (HDD). The vehicle controlsystem 447 may communicate externally using the WiMAX interface 452.

Referring now to FIG. 7B, the teachings of the disclosure can beimplemented in a WiMAX interface 468 of a cellular phone 458. Thecellular phone 458 includes a phone control module 460, a power supply462, memory 464, a storage device 466, and a cellular network interface467. The cellular phone 458 may include the WiMAX interface 468 andassociated antenna 469, a microphone 470, an audio output 472 such as aspeaker and/or output jack, a display 474, and a user input device 476such as a keypad and/or pointing device.

The phone control module 460 may receive input signals from the cellularnetwork interface 467, the WiMAX interface 468, the microphone 470,and/or the user input device 476. The phone control module 460 mayprocess signals, including encoding, decoding, filtering, and/orformatting, and generate output signals. The output signals may becommunicated to one or more of memory 464, the storage device 466, thecellular network interface 467, the WiMAX interface 468, and the audiooutput 472.

Memory 464 may include random access memory (RAM) and/or nonvolatilememory such as flash memory, phase change memory, or multi-state memory,in which each memory cell has more than two states. The storage device466 may include an optical storage drive, such as a DVD drive, and/or ahard disk drive (HDD). The power supply 462 provides power to thecomponents of the cellular phone 458.

Referring now to FIG. 7C, the teachings of the disclosure can beimplemented in a network interface 494 of a mobile device 489. Themobile device 489 may include a mobile device control module 490, apower supply 491, memory 492, a storage device 493, the networkinterface 494, and an external interface 499. The network interface 494includes a WiMAX interface and an antenna (not shown).

The mobile device control module 490 may receive input signals from thenetwork interface 494 and/or the external interface 499. The externalinterface 499 may include USB, infrared, and/or Ethernet. The inputsignals may include compressed audio and/or video, and may be compliantwith the MP3 format. Additionally, the mobile device control module 490may receive input from a user input 496 such as a keypad, touchpad, orindividual buttons. The mobile device control module 490 may processinput signals, including encoding, decoding, filtering, and/orformatting, and generate output signals.

The mobile device control module 490 may output audio signals to anaudio output 497 and video signals to a display 498. The audio output497 may include a speaker and/or an output jack. The display 498 maypresent a graphical user interface, which may include menus, icons, etc.The power supply 491 provides power to the components of the mobiledevice 489. Memory 492 may include random access memory (RAM) and/ornonvolatile memory such as flash memory, phase change memory, ormulti-state memory, in which each memory cell has more than two states.The storage device 493 may include an optical storage drive, such as aDVD drive, and/or a hard disk drive (HDD). The mobile device may includea personal digital assistant, a media player, a laptop computer, agaming console, or other mobile computing device.

Those skilled in the art can now appreciate from the foregoingdescription that the broad teachings of the disclosure can beimplemented in a variety of forms. Therefore, while this disclosureincludes particular examples, the true scope of the disclosure shouldnot be so limited since other modifications will become apparent to theskilled practitioner upon a study of the drawings, the specification andthe following claims.

1. A system, comprising: an estimation module configured to receive asignal having N sub-carriers, and generate N first estimates for channelgains of the N sub-carriers, where N is an integer greater than 1; aprocessing module configured to generate N second estimates based on theN first estimates; and a control module configured to generate Ndifferences between each of the N first estimates and corresponding onesof the N second estimates, and estimate (i) a channel gain of the signaland (ii) a preamble sequence in the signal based on the N differences.2. The system of claim 1, wherein the estimation module generates the Nfirst estimates by dividing the signal by one of i preamble sequences,where i is an integer greater than or equal to
 1. 3. The system of claim1, wherein the processing module generates each of the N secondestimates by generating weighted averages of the N first estimates. 4.The system of claim 1, wherein the processing module generates each ofthe N second estimates by processing the N first estimates using amaximum likelihood (ML) estimator or a minimum mean square error (MMSE)estimator.
 5. The system of claim 2, wherein the estimation modulegenerates i sets of the N first estimates, where each of the i sets isgenerated by dividing the signal by each of the i preamble sequences. 6.The system of claim 5, wherein the processing module generates i sets ofthe N second estimates based on the i sets of the N first estimates. 7.The system of claim 6, wherein the control module generates i sums,where each of the i sums is a sum of squares of the N differences in oneof the i sets of the N differences.
 8. The system of claim 7, whereinthe control module determines a value of i that generates a smallest ofthe i sums, estimates the preamble sequence present in the signal basedon the value of i, and estimates the channel gain based on one of the Nsecond estimates that generates the smallest of the i sums.
 9. Thesystem of claim 1, wherein the N sub-carriers are modulated usingorthogonal frequency domain multiplexing (OFDM).
 10. The system of claim9, wherein every P^(th) one of the N sub-carriers is modulated with apreamble symbol from one of i preamble sequences, where P and i areintegers greater than or equal to
 1. 11. The system of claim 10, whereinthe every P^(th) one of the N sub-carriers has substantially the samechannel phase or substantially the same differential channel phase. 12.The system of claim 10, wherein each of the i preamble sequences isdifferent from others of the i preamble sequences, the i preamblesequences have a cross-correlation value that is less than or equal to apredetermined threshold, and the i preamble sequences are stored in theestimation or the control modules.
 13. The system of claim 12, whereinthe predetermined threshold is less than approximately 0.2 for anorthogonal frequency domain multiplexing (OFDM) system using a 1024 fastFourier transform (FFT) mode.
 14. The system of claim 1, wherein thecontrol module identifies a segment of a base station that transmittedthe signal based on the preamble sequence present in the signal.
 15. Aphysical layer module (PHY) comprising: the system of claim 1; and atransceiver module configured to communicate with the estimation moduleand receive the signal.
 16. A network device comprising: the PHY ofclaim 15; and at least one antenna configured to communicate with thetransceiver module.
 17. A method for a physical layer (PHY) of a mobilestation for estimating channel gain and preamble sequence, the methodcomprising: receiving a signal having N sub-carriers at the PHY of themobile station, where N is an integer greater than 1; generating N firstestimates for channel gains of the N sub-carriers; generating N secondestimates based on the N first estimates; generating N differencesbetween each of the N first estimates and corresponding ones of the Nsecond estimates; and estimating in the PHY (i) a channel gain of thesignal and (ii) a preamble sequence in the signal based on the Ndifferences.
 18. The method of claim 17, further comprising generatingthe N first estimates by dividing the signal by one of i preamblesequences, where i is an integer greater than or equal to
 1. 19. Themethod of claim 17, further comprising generating each of the N secondestimates by generating weighted averages of the N first estimates. 20.The method of claim 17, further comprising generating each of the Nsecond estimates by processing the N first estimates using a maximumlikelihood (ML) estimator or a minimum mean square error (MMSE)estimator.
 21. The method of claim 18, further comprising generating isets of the N first estimates, where each of the i sets is generated bydividing the signal by each of the i preamble sequences.
 22. The methodof claim 21, further comprising generating i sets of the N secondestimates based on the i sets of the N first estimates.
 23. The methodof claim 22, further comprising generating i sums, where each of the isums is a sum of squares of the N differences in one of the i sets ofthe N differences.
 24. The method of claim 23, further comprisingdetermining a value of i that generates a smallest of the i sums,estimating the preamble sequence present in the signal based on thevalue of i, and estimating the channel gain based on one of the N secondestimates that generates the smallest of the i sums.
 25. The method ofclaim 17, wherein the N sub-carriers are modulated using orthogonalfrequency domain multiplexing (OFDM).
 26. The method of claim 25,wherein every P^(th) one of the N sub-carriers is modulated with apreamble symbol from one of i preamble sequences, where P and i areintegers greater than or equal to
 1. 27. The method of claim 26, whereinthe every P^(th) one of the N sub-carriers has substantially the samechannel phase or substantially the same differential channel phase. 28.The method of claim 26, further comprising storing the i preamblesequences, wherein each of the i preamble sequences is different fromothers of the i preamble sequences, and wherein the i preamble sequenceshave a cross-correlation value that is less than or equal to apredetermined threshold.
 29. The method of claim 28, wherein thepredetermined threshold is less than approximately 0.2 for an orthogonalfrequency domain multiplexing (OFDM) system using a 1024 fast Fouriertransform (FFT) mode.
 30. The method of claim 17, further comprisingidentifying a segment of a base station that transmitted the signalbased on the preamble sequence present in the signal.
 31. The method ofclaim 17, further comprising communicating with a transceiver module ina physical layer module (PHY) and receiving the signal from thetransceiver module.
 32. The method of claim 31, further comprisingcommunicating with at least one antenna of a network device comprisingthe PHY and receiving the signal via the at least one antenna.
 33. Asystem, comprising: estimation means for receiving a signal having Nsub-carriers and generating N first estimates for channel gains of the Nsub-carriers, where N is an integer greater than 1; processing means forgenerating N second estimates based on the N first estimates; andcontrol means for generating N differences between each of the N firstestimates and corresponding ones of the N second estimates, andestimating (i) a channel gain of the signal and (ii) a preamble sequencein the signal based on the N differences.
 34. The system of claim 33,wherein the estimation means generates the N first estimates by dividingthe signal by one of i preamble sequences, where i is an integer greaterthan or equal to
 1. 35. The system of claim 33, wherein the processingmeans generates each of the N second estimates by generating weightedaverages of the N first estimates.
 36. The system of claim 33, whereinthe processing means generates each of the N second estimates byprocessing the N first estimates using a maximum likelihood (ML)estimator or a minimum mean square error (MMSE) estimator.
 37. Thesystem of claim 34, wherein the estimation means generates i sets of theN first estimates, where each of the i sets is generated by dividing thesignal by each of the i preamble sequences.
 38. The system of claim 37,wherein the processing means generates i sets of the N second estimatesbased on the i sets of the N first estimates.
 39. The system of claim38, wherein the control means generates i sums, where each of the i sumsis a sum of squares of the N differences in one of the i sets of the Ndifferences.
 40. The system of claim 39, wherein the control meansdetermines a value of i that generates a smallest of the i sums,estimates the preamble sequence present in the signal based on the valueof i, and estimates the channel gain based on one of the N secondestimates that generates the smallest of the i sums.
 41. The system ofclaim 33, wherein the N sub-carriers are modulated using orthogonalfrequency domain multiplexing (OFDM).
 42. The system of claim 41,wherein every P^(th) one of the N sub-carriers is modulated with apreamble symbol from one of i preamble sequences, where P and i areintegers greater than or equal to
 1. 43. The system of claim 42, whereinthe every P^(th) one of the N sub-carriers has substantially the samechannel phase or substantially the same differential channel phase. 44.The system of claim 42, wherein each of the i preamble sequences isdifferent from others of the i preamble sequences, the i preamblesequences have a cross-correlation value that is less than or equal to apredetermined threshold, and the i preamble sequences are stored in theestimation or the control means.
 45. The system of claim 44, wherein thepredetermined threshold is less than approximately 0.2 for an orthogonalfrequency domain multiplexing (OFDM) system using a 1024 fast Fouriertransform (FFT) mode.
 46. The system of claim 33, wherein the controlmeans identifies a segment of a base station that transmitted the signalbased on the preamble sequence present in the signal.
 47. A physicallayer module (PHY) comprising: the system of claim 33; and transceivermeans for communicating with a medium, wherein the transceiver meanscommunicates with the estimation means and receives the signal.
 48. Anetwork device comprising: the PHY of claim 47; and antenna means forreceiving signals, wherein the antenna means communicates with thetransceiver means.